Adaptive filter removes variability caused by respiration from impedance cardiography signal

Abstract

Impedance cardiography (ICG) allows to measure parameters of heart mechanical function. ICG is sensitivity to movement artifacts inter alia breathing, which distorts impedance signal. Several methods were proposed to eliminate this distortion, but they cannot be used to continuous measurement or do not remove movement artifact. Adaptive filter is event-related, it learns signal characteristic within the cycle and removes components uncorrelated with the event. In this study, we compared ICG signal obtained during normal breathing with that after adaptive filtration and ICG signal obtained during momentary breath holding with this signal processed with adaptive filter. We conclude that adaptive filtering may help extract information from noisy and distorted ICG signal, but on the other hand, it may obscure some real changes in signal, for instance, rapid cyclic changes connected with respiration.